Data-intensive sociolinguistics using social media

Mikko Laitinen, Masoud Fatemi
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Abstract

This article looks into using large-scale social media data in SSH research and in particular in studies of language variation and change. It presents a case study that investigates the role of social networks in linguistic variability. Previous studies have convincingly shown that networks in which people are connected to each other in loose ties tend to contribute positively to language change. Conversely, networks in which people are closely connected to each other inhibit change. This conclusion is, however, based on small datasets, and this study tests if the difference is diluted when network size is closer to human average. The results suggest this to be the case. Towards the end, the article suggests numerous ways in which large-scale social media data and the use of data intensive methodologies could be increased and encouraged in SSH research.
使用社交媒体的数据密集型社会语言学
本文探讨了在 SSH 研究中,特别是在语言变异和变化研究中使用大规模社交媒体数据的问题。文章通过一个案例研究,探讨了社交网络在语言变异中的作用。以往的研究令人信服地表明,人与人之间联系松散的网络往往会对语言变化起到积极的促进作用。相反,人与人之间联系紧密的网络则会抑制语言的变化。然而,这一结论是基于小型数据集得出的,本研究测试了当网络规模更接近人类平均水平时,这种差异是否会被淡化。结果表明情况确实如此。文章最后提出了在社会安全和健康研究中增加和鼓励使用大规模社交媒体数据和数据密集型方法的多种途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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